In spite of major research initiatives by DARPA and other research organizations, precise indoor geolocation still remains as a challenge facing the research community. The core of this challenge is to understand the cause of large ranging errors in estimating the time of arrival (TOA) of the direct path between the transmitter and the receiver. Results of wideband measurement in variety of indoor areas reveal that large ranging errors are caused by severe multipath conditions and frequent occurrence of undetected direct path (UDP) situations. Empirical models for the behavior of the ranging error, which we refer to as the distance measurement error (DME), its relation to the distance between the transmitter and the receiver and the bandwidth of the system is needed for development of localization algorithms for precise indoor geolocation. The main objective of this dissertation is to design a direct empirical model for the behavior of the DME. In order to achieve this objective we provide a framework for modeling of DME, which relates the error to the distance between the transmitter and the receiver and bandwidth of the system. Using this framework we first designed a set of preliminary models for the behavior of the DME based on the CWINS proprietary measurement calibrated ray-tracing simulation tool. Then, we collected a database of 2934 UWB channel impulse response measurements at 3-8GHz in four different buildings to incorporate a variety of building materials and architectures. This database was used for the design of more in depth and realistic models for the behavior of the DME. The DME is divided into two components, Multipath-DME (MDME) and UDP-DME (UDME). Based on the empirical data, models for the behavior of each of these components are developed. These models reflect the sensitivity to bandwidth and show that by increasing the bandwidth MDME decreases. However in UDME the behavior is complicated. At first it reduces as we increase the bandwidth but after a certain bandwidth it starts to increase. In addition to these models through an analysis on direct path power versus the total power the average probability of having a UDP was calculated.

Recently, there has been an enormous growth of interests in geolocation applications that demand an accurate estimation of the user’s location in indoor areas. The traditional geolocation system, GPS, which was designed for being used in outdoor environments, does not perform well in indoor areas, causing frequent inaccuracies in location estimation. Therefore the need for more accurate positioning systems and even positioning techniques is a motivation for researchers to turn their attention into indoor positioning systems. In this thesis we present a unique testbed for indoor geolocation system’s real-time performance evaluation. Then we present a real-time performance evaluation of a sample indoor positioning system. We make a comparison between the simulated results of the performance evaluation of the positioning engine and the real-time performance evaluation of the positioning system. Finally, we perform a sensitivity analysis for Ekahauâ„¢ indoor positioning engine. We show that the simulation with the introduced testbed yields the same results as one would obtain by evaluating the performance of the positioning system by means of massive measurement campaigns. Running the testbed for several measurement campaigns for different scenarios enabled us to compare the results and study the effect of selected parameters on the performance of the positioning system. We also perform primitive error analysis in terms of distance error to verify the validity of the result obtained with the testbed. We show that under the same configuration both real-time performance evaluation and simulated performance evaluation will yield same result with respect to position error. We also use error modeling to determine which error model is best matched to the observed indoor positioning error. Amongst all of the possibilities of choosing methods of positioning, we focused on the Received Signal Strength (RSS) based method along with fingerprinting. Briefly said, profiles previously gathered by measurement or simulation will decide on the location of mobile terminal if a new profile comes in. It is worth mentioning that previous work similar to this testbed has been done for outdoor areas according to Ekahau's white paper. Their work is mainly focused on outdoor environment, in which multipath does not exist. In this research effort we tried to analyze the effect of different parameters on sensitivity of indoor positioning systems who suffer from multipath. Different setups for simulating real-time radio channels have been studied in literature, but still not focused on indoor areas.

Frequency domain techniques have been widely used in indoor radio propagation measurements and modeling for telecommunication applications. This work addresses measurement of the time of arrival (TOA) of the first path for geolocation applications using results of frequency domain channel measurements. First, we analyze the effect upon TOA measurement accuracy due to: sampling period of the radio channel in the frequency domain, sampling period in the time domain used for detection of the TOA and the windowing filter used before transformation to the time domain. Then, we provide some results of measurement made in line of sight (LOS) and Obstructed LOS (OLOS) indoor environments in order to compare the characteristics of the measured TOA in these two important scenarios for indoor geolocation applications. Finally, we compare the measurement results with the ray tracing based model that had been developed previously for indoor geolocation applications.

Three main elements for an indoor positioning and navigation system design are the signal structure, the signal processing algorithm and the digital and RF prototype hardware. This thesis focuses on the design and development of RF prototype hardware. The signal structure being used in the precise positioning system discussed in this thesis is a Multicarrier-Ultra Wideband (MC-UWB) type signal structure. Unavailability of RF modules suitable for MC-UWB based systems, led to design and development of custom RF transmitter and receiver modules which can be used for extensive field testing. The lack of RF design guidelines for multicarrier positioning systems that operate over fractional bandwidth ranging from 10% to 25% makes the RF design challenging as the RF components are stressed using multicarrier signal in a way not anticipated by the designers. This thesis, first presents simulation based performance evaluation of impulse radio based and multicarrier based indoor positioning systems. This led to an important revelation that multicarrier based positioning system is preferred over impulse radio based positioning systems. Following this, ADS simulations for a direct upconversion transmitter and a direct downconversion receiver, using multicarrier signal structure is presented. The thesis will then discuss the design and performance of the 24% fractional bandwidth RF prototype transmitter and receiver custom modules. This optimized 24% fractional bandwidth RF design, under controlled testing environment demonstrates positioning accuracy improvement by 2-4 times over the initial 11% fractional bandwidth non-optimized RF design. The thesis will then present the results of various indoor wireless tests using the optimized RF prototype modules which led to better understanding of the issues in a field deployable indoor positioning system.

Using Time of Arrival (TOA) as ranging metric is the most popular technique for accurate indoor positioning. Accuracy of measuring the distance using TOA is sensitive to the bandwidth of the system and the multipath condition between the wireless terminal and the access point. In a telecommunication-specific application, the channel is divided into Line of Sight (LOS) and Obstructed Line of Sight (OLOS) based on the existence of physical obstruction between the transmitter and receiver. In indoor geolocation application, with extensive multipath conditions, the emphasis is placed on the behavior of the first path and the channel conditions are classified as Dominant Direct Path (DDP), Nondominant Direct Path (NDDP) and Undetected Direct Path (UDP). In general, as the bandwidth increases the distance measurement error decreases. However, for the so called UDP conditions the system exhibits substantially high distance measurement errors that can not be eliminated with the increase in the bandwidth of the system. Based on existing measurements performed in CWINS, WPI a measurement database that contains adequate number of measurement samples of all the different classification is created. Comparative analysis of TOA estimation in different multipath conditions is carried out using the measurement database. The performance of super-resolution and traditional TOA estimation algorithms are then compared in LOS, OLOS DDP, NDDP and UDP conditions. Finally, the analysis of the effect of system bandwidth on the behavior of the TOA of the first path is presented.

In recent years there has been growing interest in ad-hoc and wireless sensor networks (WSNs) for a variety of indoor applications. Localization information in these networks is an enabling technology and in some applications it is the main sought after parameter. The cooperative localization performance of WSNs is ultimately constrained by the behavior of the utilized ranging technology in dense cluttered indoor environments. Recently, ultra-wideband (UWB) Time-of-Arrival (TOA) based ranging has exhibited potential due to its large bandwidth and high time resolution. However, the performance of its ranging and cooperative localization capabilities in dense indoor multipath environments needs to be further investigated. Of main concern is the high probability of non-line of sight (NLOS) and Direct Path (DP) blockage between sensor nodes, which biases the TOA estimation and degrades the localization performance. In this dissertation, we first present the results of measurement and modeling of UWB TOA-based ranging in different indoor multipath environments. We provide detailed characterization of the spatial behavior of ranging, where we focus on the statistics of the ranging error in the presence and absence of the DP and evaluate the pathloss behavior in the former case which is important for indoor geolocation coverage characterization. Parameters of the ranging error probability distributions and pathloss models are provided for different environments: traditional office, modern office, residential and manufacturing floor; and different ranging scenarios: indoor-to-indoor (ITI), outdoor-to-indoor (OTI) and roof-to-indoor (RTI). Based on the developed empirical models of UWB TOA-based OTI and ITI ranging, we derive and analyze cooperative localization bounds for WSNs in the different indoor multipath environments. First, we highlight the need for cooperative localization in indoor applications. Then we provide comprehensive analysis of the factors affecting localization accuracy such as network and ranging model parameters. Finally we introduce a novel distributed cooperative localization algorithm for indoor WSNs. The Cooperative LOcalization with Quality of estimation (CLOQ) algorithm integrates and disseminates the quality of the TOA ranging and position information in order to improve the localization performance for the entire WSN. The algorithm has the ability to reduce the effects of the cluttered indoor environments by identifying and mitigating the associated ranging errors. In addition the information regarding the integrity of the position estimate is further incorporated in the iterative distributed localization process which further reduces error escalation in the network. The simulation results of CLOQ algorithm are then compared against the derived G-CRLB, which shows substantial improvements in the localization performance.

"A well-known challenge in estimating the distance of the antenna pair in time-of-arrival (ToA) based RF localization systems is the problem of obstruction of the direct path (DP) between transmitter and receiver. The absence of DP component in received channel profile creates undetected direct path (UDP) conditions. UDP condition, in turn, will cause occurrence of unexpected large ranging errors which pose serious challenge to precise indoor localization. Analysis of the behavior of the ranging error in such conditions is essential for the design of precise ToA-based indoor localization systems. This dissertation discusses two open problems in ToA-based indoor localization systems. The first contribution of this dissertation discusses the problem of modeling of dynamic behavior of ranging error. We propose a novel analytical framework for analysis of dynamic spatial variations of ranging error observed by a mobile user based on an application of Markov chain. The model relegates the behavior of ranging error into four main categories associated with four states of Markov process. Parameters of distributions of ranging error in each Markov state are extracted from empirical data collected from a measurement-calibrated ray tracing algorithm simulating a typical office environment. The analytical derivation of parameters of the Markov model employs the existing path-loss models for first detected path and total multipath received power in the same office environment. Results of simulated errors from the Markov model and actual errors from empirical data show close agreement. The second contribution of this dissertation discusses the problem of identification of UDP condition given an unknown channel profile. Existing of UDP condition in a channel profile poses serious degradation to ranging estimate process. Therefore, identification of occurrence of UDP condition is of our subsequent concern. After identification, the second step is to mitigate ranging errors in such conditions. In this dissertation we present two methodologies, based on binary hypothesis testing and an application of artificial neural network design, to identify UDP conditions and mitigate ranging error using statistics extracted from wideband frequency-domain indoor measurements conducted in typical office building. "

Indoor localization remains an open problem in geolocation research, and once this is solved the localization enables counting and tracking of building occupants. This information is vital in an emergency, enables occupancy-optimized heating or cooling, and assists smart buildings in tailoring services for occupants. Unfortunately, two prevalent technologies---GPS and cellular-based positioning---perform poorly indoors due to attenuation and multipath from the building. To address this issue, the research community devised many alternatives for indoor localization (e.g., beacons, RFID tags, Wi-Fi fingerprinting, and UWB to cite just a few examples). A drawback with most is the requirement for those being located to carry a properly-configured device at all times. An alternative based on computer vision techniques poses significant privacy concerns due to cameras recording building occupants. By contrast, ILoViT research makes novel use of accelerometers already present in some buildings. These sensors were originally intended to monitor structural health or to study structural dynamics. The key idea is that when a person's footstep-generated floor vibrations can be detected and located then it becomes possible to locate persons moving within a building. Vibration propagation in buildings has complexities not encountered by acoustic or radio wave propagation in air; thus, conventional localization algorithms are inadequate. ILoVIT algorithms account for these conditions and have been demonstrated in a public building to provide sub-meter accuracy. Localization provides the foundation for counting and tracking, but providing these additional capabilities confronts new challenges. In particular, how does one determine the correct association of footsteps to the person making them? The ILoViT research created two methods for solving the data association problem. One method only provides occupancy counting but has modest, polynomial time complexity. The other method draws inspiration from prior work in the radar community on the multi-target tracking problem, specifically drawing from the multiple hypothesis tracking strategy. This dissertation research makes new enhancements to this tracking strategy to account for human gait and characteristics of footstep-derived multilateration. The Virginia Polytechnic Institute and State University's College of Engineering recognized this dissertation research with the Paul E. Torgersen Graduate Student Research Excellence Award. / Ph. D.